BP801T. BIOSTATISITCS AND RESEARCH METHODOLOGY (Theory)

About Course

Scope: To understand the applications of Biostatics in Pharmacy. This subject deals with
descriptive statistics, Graphics, Correlation, Regression, logistic regression Probability
theory, Sampling technique, Parametric tests, Non Parametric tests, ANOVA,
Introduction to Design of Experiments, Phases of Clinical trials and Observational and
Experimental studies, SPSS, R and MINITAB statistical software’s, analyzing the
statistical data using Excel. Objectives: Upon completion of the course the student shall be able to
• Know the operation of M.S. Excel, SPSS, R and MINITAB
®
, DoE (Design of
Experiment)
• Know the various statistical techniques to solve statistical problems
• Appreciate statistical techniques in solving the problems.

Recommended Books (Latest edition):
1. Pharmaceutical statistics- Practical and clinical applications, Sanford Bolton,
publisher Marcel Dekker Inc. NewYork.
2. Fundamental of Statistics – Himalaya Publishing House- S.C.Guptha
3. Design and Analysis of Experiments –PHI Learning Private Limited, R.
Pannerselvam,
4. Design and Analysis of Experiments – Wiley Students Edition,
Douglas and C. Montgomery

Course Content

Unit-I Introduction
Statistics, Biostatistics, Frequency distribution

Measures of central tendency
Mean, Median, Mode- Pharmaceutical examples Measures of dispersion: Dispersion, Range, standard deviation, Pharmaceutical problems

Correlation
Definition, Karl Pearson’s coefficient of correlation, Multiple correlation - Pharmaceuticals examples

Unit-II Regression
Curve fitting by the method of least squares, fitting the lines y= a + bx and x = a + by, Multiple regression, standard error of regression– Pharmaceutical Examples

Probability
:Definition of probability, Binomial distribution, Normal distribution, Poisson’s distribution, properties - problems Sample, Population, large sample, small sample, Null hypothesis, alternative hypothesis, sampling, essence of sampling, types of sampling, Error-I type, Error-II type, Standard error of mean (SEM) - Pharmaceutical examples

Parametric tes
t-test(Sample, Pooled or Unpaired and Paired) , ANOVA, (One way and Two way), Least Significance difference

Unit-III Non Parametric tests
Wilcoxon Rank Sum Test, Mann-Whitney U test, Kruskal-Wallis test, Friedman Test

Introduction to Research
Need for research, Need for design of Experiments, Experiential Design Technique, plagiarism

Graphs
Histogram, Pie Chart, Cubic Graph, response surface plot, Counter Plot graph

Designing the methodology
Sample size determination and Power of a study, Report writing and presentation of data, Protocol, Cohorts studies, Observational studies, Experimental studies, Designing clinical trial, various phases

Unit-IV
Blocking and confounding system for Two-level factorials

Regression modeling
Hypothesis testing in Simple and Multiple regressionmodels

Introduction to Practical components of Industrial and Clinical Trials Problems
Statistical Analysis Using Excel, SPSS, MINITAB ® , DESIGN OF EXPERIMENTS, R - Online Statistical Software’s to Industrial and Clinical trial approach

Unit-V Design and Analysis of experiments: Factorial Design
Definition, 2 2 , 23design. Advantage of factorial design

Response Surface methodology
Central composite design, Historical design, Optimization Techniques

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About Course

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Course Content

Unit-I Introduction Statistics, Biostatistics, Frequency distribution

Measures of central tendency Mean, Median, Mode- Pharmaceutical examples Measures of dispersion: Dispersion, Range, standard deviation, Pharmaceutical problems

Correlation Definition, Karl Pearson’s coefficient of correlation, Multiple correlation - Pharmaceuticals examples

Unit-II Regression Curve fitting by the method of least squares, fitting the lines y= a + bx and x = a + by, Multiple regression, standard error of regression– Pharmaceutical Examples

Parametric tes t-test(Sample, Pooled or Unpaired and Paired) , ANOVA, (One way and Two way), Least Significance difference

Unit-III Non Parametric tests Wilcoxon Rank Sum Test, Mann-Whitney U test, Kruskal-Wallis test, Friedman Test

Introduction to Research Need for research, Need for design of Experiments, Experiential Design Technique, plagiarism

Graphs Histogram, Pie Chart, Cubic Graph, response surface plot, Counter Plot graph

Designing the methodology Sample size determination and Power of a study, Report writing and presentation of data, Protocol, Cohorts studies, Observational studies, Experimental studies, Designing clinical trial, various phases

Unit-IV Blocking and confounding system for Two-level factorials

Regression modeling Hypothesis testing in Simple and Multiple regressionmodels

Introduction to Practical components of Industrial and Clinical Trials Problems Statistical Analysis Using Excel, SPSS, MINITAB ® , DESIGN OF EXPERIMENTS, R - Online Statistical Software’s to Industrial and Clinical trial approach

Unit-V Design and Analysis of experiments: Factorial Design Definition, 2 2 , 23design. Advantage of factorial design

Response Surface methodology Central composite design, Historical design, Optimization Techniques